Spatial distribution models reveal changes in potential species distribution under climate change scenarios.
Distribution models help to understand the effects that this phenomenon may cause in the future. The objective of the research was to generate a spatial distribution model of 11 forest species of temperate forests in southern Mexico; under the hypothesis that under climate change scenarios the analyzed species will experience changes in their potential distribution area. A total of 1,383 records were used, with 19 bioclimatic variables under the SSP126 and SSP585 projections to 2040 and 2100 from the CNRM-CM6-1 model, analyzed using three algorithms: Random Forest (RF), Generalized Additive Models (MAG) and Generalized Linear Models (GLM). These were evaluated using the ROC, TSS and Kappa metrics. The Random Forest model had the best performance with values above 98 % for the 11 species under study. The results show that between the scenarios there will be little change by the year 2040, as in the pessimistic scenario (SSP585) species will show a reduction in their distribution of 1.3±0.9 %, than in the optimistic scenario (SSP-126). However, by the year 2100, more significant reductions are estimated, since, in the optimistic scenario, species could reduce their distribution area by an average of 44.0 ± 9.4 %, while in the pessimistic scenario it would be reduced by 88.1 ± 6.1 %. It is expected that by the year 2100 in the SSP585 scenario all species will be severely affected, especially Pinus devoniana, which makes it imperative to establish conservation strategies as soon as possible.
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Guzmán-Santiago et al. (2025) studied this question.
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